The present disclosure relates in general to diagnostics, and in particular to techniques for generating diagnostic results in response to a diagnostic request.
Various conventional techniques exist in the industry today to perform problem diagnosis. These techniques may range from expert systems at one end of the spectrum for diagnosability to tribal knowledge forums and self-service knowledge bases at the other end. Expert systems have not been successful in establishing themselves as the de-facto tool for problem diagnosis. For example, expert systems are generally rule-based and deterministic. It can be a challenging task to determine a set of rules to correctly identify problems in a generic environment that applies to all user systems. Further, full failure data may not be readily available for problem diagnosis, often resulting in failed rule assertions. With only partially captured failure data, it is often difficult to identify an appropriate set of rules that can correctly identify the cause of a problem.
These issues are not solved by tribal knowledge forums and self-service knowledge bases. These forums and knowledge bases are based on expressing tribal knowledge in an unstructured form via text or discontinued discourse threads that may require users to tediously read, understand, and interpret the often-incomplete tribal knowledge into corrective actions. Finding the right textual documents that describe the problem is often difficult and time-consuming. Accordingly, problem diagnosis based on tribal knowledge that is expressed in unstructured forms via a knowledge base and discontinued discourse in online forums may result in incomplete or unclear problem signature and characterization. Further, these approaches may require certain subjective interpretation from users, resulting in incorrect problem isolation and identification that leads to false faults.